Robuta

https://www.mdpi.com/1424-8220/21/6/1932 Deep Neural Regression Prediction of Motor Imagery Skills Using EEG Functional Connectivity... Motor imaging (MI) induces recovery and neuroplasticity in neurophysical regulation. However, a non-negligible portion of users presents insufficient... regression predictionmotor imagery https://openreview.net/forum?id=L8nSGvoyvb Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise | OpenReview Constructing valid prediction intervals rather than point estimates is a well-established approach for uncertainty quantification in the regression setting.... quantile regressionrelaxedpredictionintervalsasymmetric https://elifesciences.org/articles/71862v1/figures Figures and data in Prediction of type 2 diabetes mellitus onset using logistic regression-based... https://www.kaggle.com/datasets/hellbuoy/car-price-prediction Car Price Prediction Multiple Linear Regression | Kaggle Predicting the Prices of cars using RFE and VIF multiple linear regressionprice predictioncarkaggle https://easychair.org/publications/preprint/rD6d Stock Price Prediction Using Linear Regression, LSTM and Decision Tree stock price predictionlinear regressionusinglstmdecision https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2024.1465604/full Frontiers | A support vector regression-based interval power flow prediction method for... In distribution networks with distributed generators (DGs), power generation and load demand exhibit increased randomness and volatility, and the line parame... support vector regression https://easychair.org/publications/preprint/rFvQT Accurate Discharge Coefficient Prediction of Streamlined Weirs by Coupling Linear Regression and... discharge coefficient https://www.sintef.no/en/publications/publication/0198cc59d7df-754d577c-49bc-421a-9c39-0052085b2709/ Exploring the possibilities of a regression model for the prediction of wetting index from crude... https://deepai.org/publication/network-regularized-sparse-logistic-regression-models-for-clinical-risk-prediction-and-biomarker-discovery Network-regularized Sparse Logistic Regression Models for Clinical Risk Prediction and Biomarker... Sep 21, 2016 - 09/21/16 - Molecular profiling data (e.g., gene expression) has been used for clinical risk prediction and biomarker discovery. However, it i... logistic regression https://www.preprints.org/manuscript/202510.1031 Variational Quantum Regression for Binding Affinity Prediction: A Hybrid Quantum-Classical... Predicting drug-target binding affinity with limited training data remains a central challenge in computational drug discovery. We introduce a hybrid... binding affinityvariationalquantumregressionprediction https://www.preprints.org/manuscript/202406.1849 An Initial Approach of Multiple Linear Regression in CO2-water Relative Permeability Prediction for... https://www.atlantis-press.com/proceedings/icemi-16/25859336 Prediction Using Logistic Regression Analysis of Peripheral Vascular Disease | Atlantis Press Logisic regression model is to study the response variable is an important analytical method for non-continuous variables. Linear regression models and... peripheral vascular diseaselogistic regressionpredictionusinganalysis https://www.mdpi.com/2071-1050/15/17/12885 Mixed Multi-Pattern Regression for DNI Prediction in Arid Desert Areas As a crucial issue in renewable energy, accurate prediction of direct normal solar irradiance (DNI) is essential for the stable operation of concentrated solar... multi patternmixedregression https://www.usgs.gov/data/data-and-model-archive-multiple-linear-regression-models-prediction-weighted-cyanotoxin Data and model archive for multiple linear regression models for prediction of weighted cyanotoxin... Multiple linear regression models were developed using data collected in 2016 and 2017 from three recurring bloom sites in Kabetogama Lake in northern... multiple linear regression https://arxiv.org/abs/2411.03753 [2411.03753] Symbolic regression via MDLformer-guided search: from minimizing prediction error to... Abstract page for arXiv paper 2411.03753: Symbolic regression via MDLformer-guided search: from minimizing prediction error to minimizing description length https://elifesciences.org/articles/71862/peer-reviews Peer review in Prediction of type 2 diabetes mellitus onset using logistic regression-based... Computational methods were used to develop accurate manual scorecards for early detection of participants at risk of type 2 diabetes based on the UK Biobank... type 2 diabetes mellitus https://jmlr.org/papers/v22/20-768.html Prediction Under Latent Factor Regression: Adaptive PCR, Interpolating Predictors and Beyond factor regressionpredictionlatent https://jmlr.org/papers/v26/25-1161.html Zono-Conformal Prediction: Zonotope-Based Uncertainty Quantification for Regression and... conformal predictionuncertainty quantificationzonobasedregression https://arxiv.org/abs/1907.11493 [1907.11493] On the variability of regression shrinkage methods for clinical prediction models:... Abstract page for arXiv paper 1907.11493: On the variability of regression shrinkage methods for clinical prediction models: simulation study on predictive... https://deepai.org/publication/prediction-intervals-and-confidence-regions-for-symbolic-regression-models-based-on-likelihood-profiles Prediction Intervals and Confidence Regions for Symbolic Regression Models based on Likelihood... Sep 14, 2022 - 09/14/22 - Symbolic regression is a nonlinear regression method which is commonly performed by an evolutionary computation method such as gen...